Osteoarthritis (OA) is the most common type of arthritis and a frequent cause of pain and disability. A major problem in the development of a pharmacologic treatment for OA is the lack of a validated non-invasive method that is both accurate and reproducible at measuring articular cartilage repeatedly with a high sensitivity for detecting disease progression. Significant progress has been made in developing MRI pulse sequences for visualizing the articular cartilage. However, despite these advances, there is great disparity in reported sensitivity and reproducibility of MRI in detecting cartilage loss, thus creating a formidable challenge for any study utilizing current MRI technology for assessing the severity and the progression of cartilage loss. Our proposal will address these concerns by introducing novel, high resolution MRI surrogate outcome measures for OA trials. We will optimize and validate novel high resolution 3D MRI techniques with high contrast and spatial resolution, namely 3D spatial-spectral spoiled gradient-echo (3D SS-SPGR), 3D steady state free precession (3D SSFP), 3D dual echo steady state (3D DESS), and 3D fast spin-echo (3D FSE) techniques obtained at 3.0T. Unlike current MRI techniques, these sequences provide improved cartilage contrast, short imaging times, and near isotropic or isotropic resolution. We will compare the accuracy of the novel high resolution techniques at 3.0T with that of standard 2D FSE and 3D SPGR techniques at 1.5T and we will correlate the imaging data in vivo with arthroscopy. We will determine the cross-sectional and longitudinal reproducibility of visual scoring and quantitative measurements of cartilage loss such as total cartilage volume and cartilage thickness for novel high resolution techniques and compare it with that of standard techniques. We will determine the sensitivity in detecting change in cartilage morphology, volume and thickness in longitudinal studies using novel high resolution 3D techniques and compare it to standard techniques. The data generated in this grant will help transform MRI into an accurate, reproducible and highly sensitive surrogate outcome measure for OA trials, an essential requirement for any current and future studies utilizing MRI in OA.